How did the robotic chef find success by turning her original customers

A few years ago, Chef Robotics encountered possible death.

“There were many dark times where I thought about abandoning,” says founder Rajat Bhageria, says TechCrunch of his six -year -old company. But friends and investors encouraged him, so he continued.

Today, Chef Robotics has not only survived, it is one of the few rallying food companies. The start, which recently set a series of $ 23 million, has 40 employees and Marquee clients such as Amy’s Kitchen and Chef Bombay. Dozens of robots that have been installed in all the US have done 45 million meals to date, says Bhageria.

This is compared to a cemetery of failed food robotic technology companies, including Chowbotics with Sally Salad Robot. Zume Pizza Robot? Robots in a food booth Crackerand, more recently, agtech Small robot company.

Bhageria says he rescued his company by doing something that early stages are afraid to do: turning away signed customers and millions of dollars in revenue.

The grip problem

It all started when Bhageria did his master’s degree in robotics in Upenn’s famed laboratory. He dreamed of Sci-Fi promised people where the robots did our housework, cut our lawns and cook our five-star dinners.

Such a world does not yet exist because engineers have not yet fully solved the robotic Caught problem. Training of the same robot to wash a glass of wine without crushing it and a cast iron without falling is a difficult task.

When it comes to robotic chefs, “no one has built a set of data on how you get a raspberry and don’t erase it, or how do you get cheese and haven’t accumulated it?” describes.

His original idea with Chef Robotics was similar to the long list of the newly established robotics that died: a robotic line for fast casual restaurants. This is a huge industry with chronic lack of workers.

“We had signed contracts, as we had signed contracts of many millions of dollars. Obviously, we don’t do it anymore, so what happened?” He said. “We couldn’t actually solve the technical problem.”

In these types of business, an employee completes an order by gathering all the varied ingredients necessary for every meal. These restaurants want the robots to reproduce this process, because the alternative is to have dozens of robots dedicated and calibrated for a single ingredient, some of which can only be used occasionally (we look at you, ants).

But Bhageria and the team were unable to build a successful pick-up-neinting robot, because there is no training data. He asked his potential customers to let him install robots for one or two ingredients, gathering training data and building there. They said no.

Then Bhageria had a superficial.

Instead of proceeding by trying to give existing customers what they wanted, maybe different customers needed. “We honestly suffered, because I spent the last year and half of my life trying to persuade these people, these fast companies, to work with us,” he recalled.

Saying it doesn’t lead to yes

It did not help that concentrating capital after 2021 was brutal. The VCs also saw the cemetery. “We talked to dozens of different chapters,” Bhageria said. “Once rejected again and again.”

Bhageria thought of abandoning. “Come home and it’s like, what am I doing in my life? I do the wrong thing? Should I stop?” He remembered.

But he dug and In March 2023, he set a round of $ 11.2 million Led by Construct Capital, while also landing controls by promus ventures, Kleiner Perkins and Gaingels.

Bhageria and the team also found their perfect purchase, a part of the food industry known as “High Mix Manufacturing”.

These are food manufacturers who have many, many recipes, and make thousands of portions, but usually as meals or lunch trays. For example salads and sandwiches or main lessons and dishes. These are meals used by airlines and hospitals, etc., or are frozen food meals for consumers.

Instead of an employee grabbing all the ingredients for each meal, “high mixing” employees form an assembly line. Each person repeatedly adds its individual ingredient to the disk until the order is complete. They then assemble the next recipe.

“There are actually hundreds of people standing in a room of 34 Fahrenheit, and they are essentially eight hours a day,” he describes. “So it’s just a terrible job.”

Consequently, this industry also has chronic labor shortages.

Robotics was not economically possible for them in the past because of the variety of components involved. But a boot that manufactures a flexible bot, where the robots are built in collaboration with the food manufacturer, projects.

Even better, “as we learn how to do this chorizo, or learn peas or this sauce or these zucchini”, the bots get real -world training data that ultimately needs to serve the restaurants quickly. Bhageria says this is still on his career map.

Best of all, thanks to VC’s regenerated interest in all things AI, the concentration of funds this time was “weird” easy, says Bhageria.

Avataar Venture Partners, co -founded by former Norwest VC Mohan Kumar, was specifically seeking to fund the “Ai in the Physical World” startups and in fact followed a robotic chef, says Bhageria. Closes this round in less than a month. Avataar drove, with existing investors making funds, Bloomberg Beta and Promus Ventures that accumulate, among others.

The new funding brings the whole chefs that rose to $ 38.8 million. A loan of $ 26.75 million was also signed by Silicon Valley Bank to fund equipment.

And the process this time was “exciting,” he said.